Instructions to use bryanhpchiang/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanhpchiang/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bryanhpchiang/test2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bryanhpchiang/test2") model = AutoModelForSequenceClassification.from_pretrained("bryanhpchiang/test2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a93e8eee28e148d8fe25ab448e76d3535fd6fd31774b1fc314f0286690189f2
- Size of remote file:
- 268 MB
- SHA256:
- 1bb39fd77304dd39dd37368f70d1afcf374d8741b74a64db84e592cdabe6aed1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.